Vestibular contribution to path integration deficits in ‘at-genetic-risk’ for Alzheimer’s disease

Abstract

AbstractPath integration changes may precede a clinical presentation of Alzheimer’s disease by several years. Studies to date have focused on how grid cell changes affect path integration in preclinical AD. However, vestibular input is also critical for intact path integration. Here, we developed a naturalistic vestibular task that requires individuals to manually point an iPad device in the direction of their starting point following rotational movement, without any visual cues. Vestibular features were derived from the sensor data using feature selection. Completing machine learning models illustrate that the vestibular features accurately classified Apolipoprotein E ε3ε4 carriers and ε3ε3 carrier controls (mean age 62.7 years), with 65% to 79% accuracy depending on task trial or algorithm. Our results demonstrate the cross-sectional role of the vestibular system in Alzheimer’s disease risk carriers and may explain individual phenotypic heterogeneity in path integration within this population